{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T19:35:38Z","timestamp":1760297738231,"version":"3.40.3"},"publisher-location":"Berlin, Heidelberg","reference-count":18,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540660699"},{"type":"electronic","value":"9783540487715"}],"license":[{"start":{"date-parts":[[1999,1,1]],"date-time":"1999-01-01T00:00:00Z","timestamp":915148800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[1999]]},"DOI":"10.1007\/bfb0098224","type":"book-chapter","created":{"date-parts":[[2006,12,7]],"date-time":"2006-12-07T14:12:49Z","timestamp":1165500769000},"page":"661-670","source":"Crossref","is-referenced-by-count":10,"title":["SA-prop: Optimization of multilayer perceptron parameters using simulated annealing"],"prefix":"10.1007","author":[{"given":"Pedro A.","family":"Castillo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan J.","family":"Merelo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jes\u00fas","family":"Gonz\u00e1lez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"V\u00edctor","family":"Rivas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gustavo","family":"Romero","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,10,30]]},"reference":[{"key":"70_CR1","volume-title":"Simulated Annealing and Boltzmann Machines","author":"EHL Aarts","year":"1989","unstructured":"E.H.L. Aarts and J. Korst. Simulated Annealing and Boltzmann Machines. John Wiley, Chichester, U.K., 1989."},{"key":"70_CR2","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1006\/jmbi.1997.0952","volume":"268","author":"C Martin San","year":"1997","unstructured":"C. San Martin; C. Gruss; J.M. Carazo. Six molecules of SV40 large tantigen assemble in a propeller-shaped particle around a channel. Journal of Molecular Biology, 268, 15\u201320, 1997.","journal-title":"Journal of Molecular Biology"},{"key":"70_CR3","unstructured":"S. Fahlman. An empirical study of learning speed in back-propagation networks Technical report, Carnegie Mellon University, 1988."},{"key":"70_CR4","unstructured":"S.E. Fahlman. Faster-Learning Variations on Back-Propagation: An Empirical Study. Proceedings of the 1988 Connectionist Models Summer School, Morgan Kaufmann, 1988."},{"key":"70_CR5","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1016\/0925-2312(94)90008-6","volume":"6","author":"W Kinnebrock","year":"1994","unstructured":"Werner Kinnebrock. A ccelerating the standard backpropagation method using a genetic approach. Neurocomputing, 6, 583\u2013588, 1994.","journal-title":"Neurocomputing"},{"key":"70_CR6","doi-asserted-by":"publisher","first-page":"975","DOI":"10.1007\/BF01009452","volume":"34","author":"S Kirkpatrick","year":"1984","unstructured":"S. Kirkpatrick Optimization by Simulated Annealing\u2014Quantitative Studies. J. Stat. Phys. 34, 975\u2013986, 1984.","journal-title":"J. Stat. Phys."},{"key":"70_CR7","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1023\/A:1009617113191","volume":"8","author":"JJ Merelo","year":"1998","unstructured":"J.J. Merelo; A. Prieto; F. Moran; R. Marabini and J.M Carazo. Automatic Classificati of Biological Particles from Electron-microscopy Images Using Conventional and Genetic-algorithm Optimized Learning Vector Quantization. Neural Proccessing Letters 8: 55\u201365, 1998, 1998.","journal-title":"Neural Proccessing Letters"},{"key":"70_CR8","doi-asserted-by":"crossref","unstructured":"Zbigniew Michalewicz. Genetic Algorithms + Data Structures = Evolution Programs, Second, Extended Edition. Springer-Verlag, 1994.","DOI":"10.1007\/978-3-662-07418-3"},{"key":"70_CR9","unstructured":"D.J. Montana and L. Davis. Training feedforward neural networks using genetic algorithms. Proc. 11th Internat. Joint Conf. on Artificial Intelligence, 762\u2013767, 1989."},{"key":"70_CR10","doi-asserted-by":"publisher","first-page":"1052","DOI":"10.1007\/3-540-59497-3_284","volume":"930","author":"V Vergara","year":"1995","unstructured":"V. Vergara; S. Sinne; C. Moraga. Optimal Identification Using Feed-Forward Neural Networks. Lectures Notes in Computer Science, vol. 930, 1052\u20131059, 1995.","journal-title":"Lectures Notes in Computer Science"},{"key":"70_CR11","series-title":"Technical Report 21\/94","volume-title":"PROBEN1\u2014A set of benchmarks and benchmarking rules for neural network training algorithms","author":"L Prechelt","year":"1994","unstructured":"Lutz Prechelt. PROBEN1\u2014A set of benchmarks and benchmarking rules for neural network training algorithms. Technical Report 21\/94, Fakult\u00e4t f\u00fcr Informatik, Universit\u00e4t Karlsruhe, D-76128 Karlsruhe, Germany, September 1994. Anonymous FTP: \/pub\/papers\/techreports\/1994\/1994-21.ps.Z on ftp.ira.uka.deurl"},{"key":"70_CR12","unstructured":"P.A. Castillo; J. Gonzalez; J.J. Merelo; V. Rivas; G. Romero; A. Prieto. G-Prop: Global Optimization of Multilayer Perceptrons using GAs. submitted to Neurocomputing, 1998."},{"key":"70_CR13","unstructured":"M. Riedmiller. Description and Implementation Details. Technical report, University of Karlsruhe, 1994."},{"key":"70_CR14","doi-asserted-by":"crossref","unstructured":"M. Riedmiller and H. Braun. A Direct Adaptive Method for Faster Backpropagation Learning; The RPROP Algorithm. In Ruspini, H., (Ed.) Proc. of the ICNN93, San Francisco, pp. 586\u2013591, 1993.","DOI":"10.1109\/ICNN.1993.298623"},{"key":"70_CR15","unstructured":"O. L. Mangasarian; R. Setiono and W.H. Wolberg. Pattern recognition via linear programming: Theory and application to medical diagnosis. Large-scale numerical optimization, Thomas F. Coleman and Yuying Li, editors, SIAM Publications, Philadelphia 1990, pp 22\u201330, 1990."},{"key":"70_CR16","doi-asserted-by":"crossref","unstructured":"T. Tambouratzis. Simulated Annealing Artificial Neural Networks For the Satisfiability (SAT) Problem. Artificial Neural Nets and Genetic Algorithms, 340\u2013343, 1995.","DOI":"10.1007\/978-3-7091-7535-4_89"},{"key":"70_CR17","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1063\/1.1699114","volume":"21","author":"N Metropolis","year":"1958","unstructured":"N. Metropolis; A.W. Rosenbluth; M.N. Rosenbluth; A.H. Teller; E. Teller. Equations of State Calculations by Fast Computing Machines. J. Chem. Phys. 21, 1087\u20131092, 1958.","journal-title":"J. Chem. Phys."},{"key":"70_CR18","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1126\/science.220.4598.671","volume":"220","author":"S Kirkpatrick","year":"1983","unstructured":"S. Kirkpatrick; C.D. Gerlatt; M.P. Vecchi. Optimization by Simulated Annealing. Science 220, 671\u2013680, 1983.","journal-title":"Science"}],"container-title":["Lecture Notes in Computer Science","Foundations and Tools for Neural Modeling"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/BFb0098224","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,22]],"date-time":"2019-04-22T15:42:36Z","timestamp":1555947756000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/BFb0098224"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999]]},"ISBN":["9783540660699","9783540487715"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/bfb0098224","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[1999]]}}}